Digital Commons Network^™

Olac Best Practices For Cataloging Dvd-Video And Blu-Ray Discs, Objects, Streaming Media, Video Games, And Digital Media Storage Devices Using The Original Rda Toolkit And Marc 21, Kristi Bergland, Mary Huismann, John Dickson, Autumn Faulkner, Robert B. Freeborn, Jeannette Ho, Sarah Hovde, Kyla Jemison, Yoko Kudo, Junghae Lee, Jack Nighan, Alex Whelan

OLAC Publications and Training Materials

The OLAC Unified Best Practices Guide brings together the current published best practice guides into a single best practices guide that incorporates Best Practices for Cataloging DVD-Video and Blu-ray Discs Using RDA and MARC21, Best Practices for Cataloging Objects Using RDA and MARC 21, Best Practices for Cataloging Streaming Media Using RDA and MARC21, Best Practices for Cataloging Video Games Using RDA and MARC21, and Best Practices for Cataloging Digital Media Storage Devices Using RDA and MARC21.

Chaotropic And Kosmotropic Effects Of Brines On Protein Structure: Habitability Across The Solar System, Shelby Dawn Osborne

Graduate Theses and Dissertations

Salts exhibit unique and specific effects on biomolecular structure depending on the physical nature of the salt (ion density, formation of hydration shells, direct binding to protein). This thesis implements biochemical, thermodynamic, and computational methods to investigate how the nature of the salt effects protein structure, which aids in defining the habitability of various brine solutions. By using simple proteins and solar system relevant salts, we inspect the physical reactions of proteins to these saltwater environments to understand which salts stabilize or destabilize protein structure. Several methods of experimentation are utilized to provide an understanding of the interaction relevant to …

Jme 4110: E-Bike Power Take-Off Device, Masa Marmarchi, Anna Favaron, Alexis Brutcher, Julie Steiger, Ava Le

Washington University / UMSL Mechanical Engineering Design Project JME 4110

This project focuses on developing a portable power solution that allows an E-bike battery to be used to power small devices during emergency situations. The system is designed to provide a convenient alternative when traditional sources of electricity are unavailable, while remaining safe, practical, and easy to store and use with the E-bike. The final design combines the necessary electrical components with a compact storage solution, allowing the system to be carried with the bike and used when needed.

Jme 4110: Drill-Powered Beach Umbrella Anchor, Matthew Barton, Tanin Ramnath, Marquan Bailey, Zachary Van-Horn, Kaelin Mendoza

Washington University / UMSL Mechanical Engineering Design Project JME 4110

A common and potentially hazardous situation faced by beachgoers is when standard umbrella anchors fail to hold during wind gusts, causing the umbrella to potentially go airborne and injure nearby people. Existing anchors require manual operation, leading to inconsistent grip and no resistance to different wind directions. Our project is a motorized three anchor system that drives augers into the sand to ensure a consistent grip and security against the wind.

Jme 4110: Drill Powered Pressure Washer, Kathryn Keele, Ashley Givance, Reagan Grass, Andrew Ellis, Jacob Thebeau

Washington University / UMSL Mechanical Engineering Design Project JME 4110

This project focuses on developing a drill-powered pressure washer attachment that connects to a standard cordless drill and garden hose. The device uses the drill as its only power source to pressurize water for cleaning applications. This portable design provides a convenient, low-cost alternative to traditional electric or gas-powered pressure washers.

The Geologic History Of The Chehalis Forearc Basin, Washington State, Usa, R. L. Moe, J. Bershaw, L. M. Staisch, A. R. Streig

Geology Faculty Publications and Presentations

The Chehalis basin is located between the Cascade arc and the Coast Range in southwest Washington State. It consists of sedimentary and volcanic rocks deposited throughout the Cenozoic and is underlain by the Siletzia terrane, a thick, large igneous province accreted in the Eocene. Here, we constrain evolution of the Chehalis basin depocenter using isochore maps derived from isostatic gravity anomalies, borehole data, and stratigraphy for several time periods: the Eocene (47.6–36.8 Ma), the Oligocene (36.8–20 Ma), and the Neogene (20–0 Ma). Our results suggest that local subsidence is driven by deformation on faults that bound and intersect the basin. …

Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas

Computer Science Faculty Research & Creative Works

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, …

Scattered Hypothesis Generation For Open-Ended Event Forecasting, He Chang, Zhulin Tao, Lifang Yang, Xianglin Huang, Yunshan Ma

Research Collection School Of Computing and Information Systems

Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic uncertainty of real-world events. To bridge this gap, we advance open-ended event forecasting from pinpoint forecasting to scatter forecasting by introducing the proxy task of hypothesis generation. This paradigm aims to generate an inclusive and diverse set of hypotheses that broadly cover the space of plausible future events. To this end, we propose SCATTER, a reinforcement learning framework that jointly optimizes inclusiveness and diversity of the hypothesis. Specifically, we design a novel hybrid reward that consists of …

Mab-Dqa: Addressing Query Aspect Importance In Document Question Answering With Multi-Armed Bandits, Yixin Xiang, Yunshan Ma, Xiaoyu Du, Yibing Chen, Yanxin Zhang, Jinhui Tang

Research Collection School Of Computing and Information Systems

Document Question Answering (DQA) involves generating answers from a document based on a user’s query, representing a key task in document understanding. This task requires interpreting visual layouts, which has prompted recent studies to adopt multimodal Retrieval-Augmented Generation (RAG) that processes page images for answer generation. However, in multimodal RAG, visual DQA struggles to utilize a large number of images effectively, as the retrieval stage often retains only a few candidate pages (e.g., Top-4), causing informative but less visually salient content to be overlooked in favor of common yet low-information pages. To address this issue, we propose a Multi-Armed Bandit–based …

Purifai: Detecting And Fixing Search-Induced Distortions In Web-Augmented Llms, Guoqing Wang, Zhao Zhang, Zeyu Sun, Xiaofei Xie, Yizhou Chen, Yanchao Tan, Dan Hao

Research Collection School Of Computing and Information Systems

As Large Language Models (LLMs) increasingly serve as interfaces for proprietary data (e.g., enterprise knowledge bases, legal statutes), ensuring their fidelity to trusted internal information is paramount. While integrating real-time web search can enhance model utility, it introduces a critical vulnerability: the ingestion of conflicting, misleading, or hallucinated content from the open web can override the model's adherence to its verified internal knowledge. We define this failure mode as search-induced distortion, a significant risk in high-stakes domains where the internal knowledge base serves as the absolute ground truth.To address this challenge, we present PurifAI, a proactive, model-agnostic, cache-level purification system …

Generation-Augmented Video Corpus Moment Retrieval, Mingjin Kuai, Qianyin Xiao, Juncheng Li, Jin Peng, Lizi Liao, Wei Ji

Research Collection School Of Computing and Information Systems

Video Corpus Moment Retrieval (VCMR) requires models to efficiently retrieve and precisely locate specific moments relevant to natural language queries within a massive, untrimmed video corpus. However, existing discriminative approaches typically rely on shallow visual-textual feature matching mechanisms, which often struggle to capture fine-grained semantic differences. To address this limitation, we propose Video-GAR, a novel framework that reframes the conventional retrieval task from superficial matching to generative understanding, positing that the capability for query reconstruction evidences deep semantic comprehension. Specifically, Video-GAR orchestrates three synergistic components: To overcome the computational efficiency bottleneck, we construct a Bi-Mamba backbone that leverages the linear …

Bridging Llm Embeddings And Vae Parameters For Disentangled Recommendation, Nhu-Thuat Tran, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Disentangled recommendation within the Variational Autoencoder (VAE) framework aims to capture multiple user interests. While effective, these VAEs are fundamentally constrained by their reliance on interaction data alone, lacking the rich external semantic knowledge needed to properly structure and separate latent interests. Meanwhile, Large Language Models (LLMs) excel at deriving profound user preference signals from textual data. Prevailing methods for integrating LLMs into recommendation, however, either focus on single-interest modeling or perform a shallow fusion by aligning LLM and VAE representation spaces. Thus, they fail to fundamentally shape the VAE's latent space for multi-interest learning, hindering recommendation performance. To bridge …

A Refined Generalization Analysis For Extreme Multi-Class Supervised Contrastive Representation Learning, Minh Hieu Nong, Antoine Ledent

Research Collection School Of Computing and Information Systems

Contrastive Representation Learning (CRL) has achieved strong empirical success in multiple machine learning disciplines, yet its theoretical sample complexity remains poorly understood. Existing analyses usually assume that input tuples are identically and independently distributed, an assumption violated in most practical settings where contrastive tuples are constructed from a finite pool of labeled data, inducing dependencies among tuples. While one recent work analyzed this learning setting using U-Statistics to estimate the population risk, the techniques used therein require the risk of each class to concentrate uniformly, making excess risk bounds scale in the order of where denotes the probability of the …

Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen

Journal of System Simulation

Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on …

Research On Safety Monitoring System For Digital Twin Fully Mechanized Mining Face In Thin Coal Seams, Ya Liu, Zhaoyun Zhang, Cheng An, Canguang Zheng

Journal of System Simulation

Abstract: To solve the problems of opaque production processes, difficult expression of production information, and high difficulty in real-time model driving and safety monitoring in fully mechanized mining faces of thin coal seams, studying the use of digital twin technology and risk early warning models to solve beyond-visual-range visual production operations and safety monitoring control of the working face has important theoretical and practical value. This paper studied the construction methods of the digital twin system for fully mechanized mining faces in thin coal seams and discussed the construction of high-precision three-dimensional models, the real-time collection and processing conversion of …

Research On Multi-Objective Hybrid Flow-Shop Scheduling With Order Splitting, Junjie Yu, Weixi Ji, Chen Chen, Jingyu Lu, Chaoyang Zhang

Journal of System Simulation

Abstract: To address the order splitting multi-objective hybrid flow-shop scheduling problem (OSMOHFSP), a dual-objective optimization model was formulated with the objectives of minimizing makespan and total order tardiness. Fixed sub-batch specification constraints were incorporated to reflect common splitting limitations in actual production. A sub-batch generation strategy based on a candidate set of sub-batch specifications was designed to efficiently filter feasible splitting combinations, effectively reducing the search space dimensionality and computational complexity. A hybrid multi-objective metaheuristic algorithm integrating NSGA-II and SA was proposed. The global search capability was enhanced by constructing two crossover and four mutation operators. An improved SA embedding …

Ultra-Short-Term Photovoltaic Power Prediction Method Based On Spatio-Temporal Feature Enhancement Of Ground-Based Cloud Images, Zhiwei Kou, Fengyue Xin, Xiaoming Cui, Yu Yin, Feifan Li, Yongsheng Qi

Journal of System Simulation

Abstract: In view of the time lag in ground-based cloud image acquisition and the insufficient accuracy of existing photovoltaic power prediction models, an ultra-short-term photovoltaic power prediction method named spatial-temporal feature enhancement-ground-based cloud image-improved LSTM (STFE-GCI-ILSTM), which is based on spatio-temporal feature enhancement-ground-based cloud images-improved long short-term memory (LSTM) network was proposed. A ground-based cloud image prediction model with multi-scale spatio-temporal feature enhancement (STFE-GCI) was constructed. By spatial feature enhancement, temporal feature enhancement, and multi-scale feature fusion technologies, the deep spatio-temporal features of historical cloud image sequences were extracted to generate future predicted cloud image sequences, thereby eliminating the time …

Prediction Of Industrial Concentration Parameters Based On Caudformer Model, Kaipeng Xu, Yan Wang, Xin Zhang, Yang Liu, Zhenzhong Wang, Xiang Liu, Zhicheng Ji

Journal of System Simulation

Abstract: To solve the problems in the industrial concentration process of traditional Chinese medicine that traditional prediction methods are difficult to deal with complex characteristics such as nonlinearity, high-dimensional coupling, and highly skewed distribution and that existing deep learning models insufficiently consider causal relationships among variables, ignore frequency-domain periodic characteristics, and lack long-range dependency modeling capabilities, an improved multivariate time series prediction model CauDformer was proposed in this paper. Based on the iTransformer architecture, a causal multi-head self-attention mechanism (C-MHSA) was introduced to compulsorily constrain the dependency direction among variables by utilizing a lower triangular causal mask, guiding the model …

Accountable Agents In Software Engineering: An Analysis Of Terms Of Service And A Research Roadmap, Christoph Treude

Research Collection School Of Computing and Information Systems

AI coding assistants and autonomous agents are becoming integral to software development workflows, reshaping how code is produced, reviewed, and maintained. While recent research has focused mainly on the capabilities and impacts of productivity of these systems, much less attention has been paid to accountability: who is responsible when agents generate, modify, or recommend code? In practice, accountability is defined through the Terms of Service (ToS) and related policy documents that govern the use of AI-powered development tools.In this vision paper, we present a comparative analysis of the Terms of Service for widely used AI coding assistants and agent-enabled development …

A Framework For Top-K Queries With Constrained Preferences, Kyriakos Mouratidis, Nikolaos Chaloulakos, Bo Tang

Research Collection School Of Computing and Information Systems

Traditional rank-aware processing assumes a dataset that contains available options to cover a specific need (e.g., restaurants, hotels, etc) and users who browse that dataset via top-k queries with linear scoring functions, i.e., by ranking the options according to the weighted sum of their attributes, for a set of given weights. In practice, however, user preferences (weights) may only be estimated with bounded accuracy, or may be inherently imprecise due to the inability of a human user to specify exact weight values with absolute accuracy. Motivated by this, we define the constrained-preference top-k (CT) query. Given an approximate description of …

Spatiotemporal Sycophancy: Negation-Based Gaslighting In Video Large Language Models, Ziyao Tang, Pengkun Jiao, Bin Zhu, Huiyan Qi, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under conversational interaction remains largely underexplored. In this paper, we identify spatiotemporal sycophancy, a failure mode in which Vid-LLMs retract initially correct, visually grounded judgments and conform to misleading user feedback under negation-based gaslighting. Rather than merely changing their answers, the models often fabricate unsupported temporal or spatial explanations to justify incorrect revisions. To systematically investigate this phenomenon, we propose a negation-based gaslighting evaluation framework and introduce GasVideo-1000, a curated benchmark designed to probe spatiotemporal sycophancy with clear visual grounding and temporal reasoning requirements. …

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

From Gap To Growth: Academic Librarian Perspectives On Why Collaboration And Curriculum Matter, Stephanie Hallam

Library Faculty Scholarship

Incoming undergraduate students possess information literacy skillsets impacted by several factors, such as prior development of information literacy skills, librarian-faculty collaboration, and GenAI advancements. Academic librarians’ perspectives on undergraduate students’ library use and information literacy skills were examined via a 2025 survey of 337 undergraduate academic librarians. Using the Pearson bivariate method, the authors identified themes pertaining to the challenges students face as well as librarian-proposed solutions. Open responses from librarians provide additional insights. The results showed that librarians desire faculty partnerships and collaborative library instruction to improve information literacy skills and library use.

Empowering Domestic Violence Survivors Through Community-Based Self-Regulation Suppor, Xen Gabrielle O. Advincula

Occupational Therapy Student Capstones

Purpose: Program development of trauma-informed, occupation-based resources and program and incorporating OT-related principles to support occupational balance and engagement of survivors of DV and IPV

Goal: Enhance and support the staff’s capacity and understanding of OT-scope in community settings and incorporation of OT-focused self-regulation strategies

Outcome: Increase the staff’s confidence levels of knowledge on the scope of OT within community-based settings and OT-related strategies to support self-regulation levels

An Epilepsy Community Collective Towards Occupational Justice And Empowerment, Tyler Debuty

Occupational Therapy Student Capstones

Underutilization of epilepsy-specific resource programs, lack of public awareness about epilepsy, limitations in community belonging, and implications for self-management programs aimed towards improving quality of life and reducing the burden of care during the transition into adulthood and throughout the lifespan for people with epilepsy.

Improving Quality Of Life For Informal Caregivers Of Post-Stroke Survivors: Implementing Preventative, Advocacy And Educational Strategies, Joann Bennett

Occupational Therapy Student Capstones

Stroke recovery extends beyond hospital discharge, yet community-dwelling stroke survivors and their informal caregivers often have limited access to continued education, wellness resources, and community-based support.

This gap contributes to caregiver burden, reduced occupational participation, and decreased quality of life.

Occupational Therapy Approaches To Mitigating Cancer-Related Fatigue (Crf): A Scoping Review And Practice Framework, Brooke Carson

Occupational Therapy Student Capstones

Goal: Improve knowledge and competence in CRF management through evidence-based education to improve CRF interventions in oncology rehabilitation

Outcome: Increased confident and application of evidence based CRF intervention strategies, leading to improved functional performance and occupational engagement for individuals experiencing CRF

Enhancing New Mother's Mental Health And Confidence After Discharge, Breana De La Cruz

Occupational Therapy Student Capstones

New mothers lack guidance, education and resources for common postpartum complications resulting in a decreased overall wellbeing in the postpartum period.

Post-Stroke Fatigue: Bridging Neuropathology And Neurorehabilitation-Translating Research Into Clinical Assessment And Intervention Strategies, Wesley Green

Occupational Therapy Student Capstones

Current clinical approaches to post-stroke fatigue are challenged by limited evidence and an incomplete understanding of its underlying mechanisms.

Kickin' It Old School: Connecting The Ages, Elyssia Lambert

Occupational Therapy Student Capstones

Problem Statement

Lack of social participation is associated with negative impacts on QoL in individuals with dementia

Lack of awareness and knowledge of OT as a career option